• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.2
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• pp.40-45
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• 2007

This study analyzed the resistivity characteristic of model block to make the good use of structure grounding and substitution grounding electrode base of building. After making the model block of mortar and concrete block, it measured resistivity in hydrous condition and dry condition and compared with the blocks that is mixed earth resistance lowering agent to decrease resistivity. The resistance value of block accepted much influence by block resistivity. When the block resistivity was same or similar value, the value of soil resistivity has occurred as different as the value of grounding resistance.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.807-822
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• 2021

Various accuracy measures that can be explained on the odds curve are discussed, and an alternative accuracy measure, the maximum square, is proposed based on the characteristics of the odds curve. Thresholds corresponding to these accuracy measures are obtained by considering various probability distribution functions and an illustrative example. Their characteristics are discussed while comparing many kinds of statistics measuring thresholds. Therefore, we can conclude that optimal thresholds could be explored from the odds curve, similar to the ROC curve, and that the maximum square measure can be used as a good accuracy measure that can improve the performance of the binary classification model.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.64-74
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• 2019

Although a non-rigid registration has high demands in clinical practice, it has a high computational complexity and it is very difficult for ensuring the accuracy and robustness of registration. This study proposes a method of applying a non-rigid registration to 3D magnetic resonance images of brain in an unsupervised learning environment by using a deep-learning network. A feature vector between two images is produced through the network by receiving both images from two different patients as inputs and it transforms the target image to match the source image by creating a displacement vector field. The network is designed based on a U-Net shape so that feature vectors that consider all global and local differences between two images can be constructed when performing the registration. As a regularization term is added to a loss function, a transformation result similar to that of a real brain movement can be obtained after the application of trilinear interpolation. This method enables a non-rigid registration with a single-pass deformation by only receiving two arbitrary images as inputs through an unsupervised learning. Therefore, it can perform faster than other non-learning-based registration methods that require iterative optimization processes. Our experiment was performed with 3D magnetic resonance images of 50 human brains, and the measurement result of the dice similarity coefficient confirmed an approximately 16% similarity improvement by using our method after the registration. It also showed a similar performance compared with the non-learning-based method, with about 10,000 times speed increase. The proposed method can be used for non-rigid registration of various kinds of medical image data.

• Korean Journal of Soil Science and Fertilizer
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• v.21 no.4
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• pp.367-372
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• 1988

A series of field experiment was conducted to find out error range and to compare precision based on error analysis of soil water content measured with gravimetric, surface & depth neutron and gypsum block methods in a sandy loam soil. The error of soil water content measured with gravimetric (core-sampling), surface and depth neutron method showed quardratic curve, whereas that with gypsum block was exponential curve in relation to soil water content. Within the range of volumetric soil water content from 11 to 33%, the error of soil water content measured with gravimetric, surface neutron, depth neutron and gypsum block method was ranged from 0.28 to 3.49%, 0.71 to 2.63%, 0.52% to 1.01% and 0.05 to 21.89%, respectively. The error of soil water content measured with depth neutron method was lower than those of other methods, when the soil water content was more than 14% in sandy loam soil. The relative number of replicates of soil water measurement for surface neutron, depth neutron and gypsum block method to attain same precision for gravimetric method was 0.6-1.7, 0.07-0.8 and 0.1-125, respectively.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.13-24
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• 2013

IEEE 802.15.4 network and WiFi network are installed to overlap each other and configured to use adjacent frequency bands in which case the communication service required by applications can not be guaranteed because of randomly increased frame transmission delay and frequent frame transmission failures at nodes in IEEE 802.15.4 network. In this paper, transmission delay model at IEEE 802.15.4 nodes and an experimental system to evaluate the interference from WiFi traffic are described, then elements for the evaluation of interference are measured with the analysis of their characteristics. A sequential method of using medium access layer and physical layer elements of IEEE 802.15.4 protocols is proposed to decide interference from WiFi network. With the proposed method, if an evaluation function having frame transmission failures and transmission delay as variables returns a value greater than a threshold, intensive measurements of wireless channel power are carried out subsequently and the final decision of interference is made by the calculated average channel power. Experimental results of the method show that the decision time is reduced with increased frequency of decision in comparison to an other similar method.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.429-429
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• 2021

2019년 발생한 인천광역시 붉은 수돗물 사태로 급수구역에 포함된 26만 1천 세대, 63만 5천 명이 직·간접적인 피해를 입은 바 있다. 경제적 피해액으로 추정할 경우 최소 1,280억 원 이상으로 보고된 바 있으며, 이와 같은 상수관망의 수질사고 확산은 장기간 동안 시민의 건강과 생활환경 수준을 저하시킨다. 따라서 상수도시스템의 수질사고확산 모델링 및 방지기술을 통한 수질안전성의 재확인이 필요하며, 이것은 상수도시스템의 지속가능성을 높여 국민이 체감하는 물 환경 수준 제고에 기여가 가능하다. 관망 내 수질해석을 직접적으로 수행하는 모델은 국외적으로 다양하게 개발(PODDS, EPANET-MSX, EPANET2.2 등)된 바 있으나 검·보정을 위한 수질측정 자료 부족 등으로 적용이 제한적이라는 한계가 현재에도 존재한다. 이를 보완하기 위해 수질자료에 비해 그 양이 많고 획득방법이 상대적으로 수월한 수리학적 계측자료 및 해석결과를 활용한 관로 내 체류시간 등을 활용한 연구가 수행된 바 있다. 그러나 이와 같은 수리학적 해석 결과를 활용하는 경우에도 계측자료를 기반으로 한 수리학적 검·보정은 필수적이라 할 수 있다. 본 연구에서는 관로 내 체류시간에 직접적인 영향을 미치는 유량 및 유속자료를 중심으로 수리학적 관망해석의 결과를 최적 검·보정하는 방법론을 제안하였다. 기존 상수관망 수리해석의 검·보정은 일부 지점에서 수압을 측정하고, 수리해석 결과로 도출되는 해당 지점의 수압이 실측된 결과와 유사하도록 관로의 유속계수를 적절히 보정하는 형태로 진행되었다. 그러나 본 연구에서는 관로유량과 유속자료의 목적함수 내 가중치를 수압자료보다 크게 설정하여 체류시간 중심의 검·보정이 수행될 수 있도록 하였으며, 검·보정 대상인자 역시 대수용가의 수요량, 수요패턴, 그리고 관로유속계수로 확장된 모형을 구축하였다. 최적화 기법으로는 메타휴리스틱 기법중 하나인 화음탐색법을 활용하였다. EPANET 2.2 Toolkit과 Visual Basic .Net을 연계하여 프로그래밍하였으며, 개발된 모형을 실제 지방상수도 시스템에 적용하여 분석하였다.

• Journal of Animal Science and Technology
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• v.50 no.5
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• pp.581-590
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• 2008

Growth curves for ultrasonic carcass traits such as longissimus muscle area, backfat thickness and marbling score as well as chest girth which was simultaneously measured when carcass traits were investigated using ultrasound measuring technique were estimated to identify growth patterns and to adjust maturing effects in order to evaluating genetic merits on cows in farming basis. 27,410 records from 22,451 cows on which of 15~90 month of age were investigated from the national wide of Korea using by ultrasonic scanning techniques by the skilled persons from 2002 to 2007. Van Bertalanffy growth function was applied for estimating growth curves on these traits. Carcass traits and chest girth would be linearly increased by body condition score. It might be used for multiplicative correction factors for pre- adjustment on the body condition scores. Growth pattern on chest girth would be quickly reached to mature size and stable on after reached to asymptotic mature size. Longissimus muscle area would also be reached to mature size but little smoother than chest girth. Otherwise, growth curve on backfat thickness would be steadily increasing up to 7 years of age. It also showed large individual difference by way of mean square error. Marbling score would be steadily increased but sharper than those on backfat thickness. It would be reached to mature size up at 5 years of age. Those growth curves would be used for correcting function on age at investigating on genetic evaluation system.

• Journal of the Korea Organic Resources Recycling Association
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• v.22 no.1
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• pp.27-34
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• 2014

demand for a low-cost treatment technology is high because the sewage sludge has an 80% or higher water content and a high energy consumption cost. This study apply the thermal hydrolysis reaction that consumes a small amount of energy for sludge treatment. The purpose of this study is to quantify the viscosity of sewage sludge according to reaction temperature. we measured continuously the torque of dewatered sludge by the reaction temperature. As the reaction temperature increased, the dewatered sludge is thermal hydrolysis under a high temperature and pressure. Therefore, the bond water in the sludge cells comes out as free water, which changes the dewatered sludge from a solid phase to slurry of a liquid phase. The results of the viscosity measurements according to the reaction temperature showed that the viscosity was very high at $270,180kg/m{\cdot}sec$ at a temperature of 293K, but rapidly decreased with increases in the reaction temperature to $12kg/m{\cdot}sec$ at a temperature of 400K and to $4kg/m{\cdot}sec$ at a temperature of 460K or higher, similar to the changes in the viscosity of water. And we was obtained the viscosity function of boundary condition for the optimal design of thermal hydrolysis reactor by numerical modeling based on the this results.

• Journal of Information Management
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• v.40 no.4
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• pp.135-150
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• 2009

Existing bibliometric laws have been established on the basis of well defined science journals with a long history. However, the history of technology innovation research in Korea is young and the scope of the research is diverse compared with other fields. The main purpose of this research can be summarized as follows : Can the traditional bibliometric laws be used to explain the young and diverse data derived from technology innovation studies in Korea. Second, we want to compare the explain ability of the power law, compared with the traditional laws in the field. Third, we propose a quasi index related to the well-known impact factor to measure the contribution of a journal or a group of journals to the development of innovation research in Korea. We confirmed Lotka's and Bradford's laws which are used to measure the productivity of researchers, but we could not support the validity of Price's Square Root law as Nicholls (1998) could not. On the citations to journals, Garfield's laws is not observed. However, the power law fits well the citations to author, journal, article, and book. The estimated parameters between 1.6 and 3.5 are similar to the values in the range of 1.5 and 3 in previous studies. Finally the quasi index shows that the influence of international leading journals on innovation research in Korea is weaker than on innovation studies in the world.

• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.295-302
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• 2022

Sparse-view computed tomography (CT) imaging technique is able to reduce radiation dose, ensure the uniformity of image characteristics among projections and suppress noise. However, the reconstructed images obtained by the sparse-view CT imaging technique suffer from severe artifacts, resulting in the distortion of image quality and internal structures. In this study, we proposed a convolutional neural network (CNN) with wavelet transformation and residual learning for reducing artifacts in sparse-view CT image, and the performance of the trained model was quantitatively analyzed. The CNN consisted of wavelet transformation, convolutional and inverse wavelet transformation layers, and input and output images were configured as sparse-view CT images and residual images, respectively. For training the CNN, the loss function was calculated by using mean squared error (MSE), and the Adam function was used as an optimizer. Result images were obtained by subtracting the residual images, which were predicted by the trained model, from sparse-view CT images. The quantitative accuracy of the result images were measured in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The results showed that the trained model is able to improve the spatial resolution of the result images as well as reduce artifacts in sparse-view CT images effectively. Also, the trained model increased the PSNR and SSIM by 8.18% and 19.71% in comparison to the imaging model trained without wavelet transformation and residual learning, respectively. Therefore, the imaging model proposed in this study can restore the image quality of sparse-view CT image by reducing artifacts, improving spatial resolution and quantitative accuracy.